Agents & sessionsSkill
EverOS
EverMind-AI
One portable memory layer for every AI agent: local-first, Markdown-native, user-owned, and self-evolving across apps, tools, and workflows.
Structure check pending
agent-memoryagentic-aiaichats
Back to Marketplace
Agents & sessionsPlugin
dsh-flow
rootkiller6788/dsh-flow
dsh-flow is a tool for DeepSeek Harness. dsh-flow —— DeepSeek Harness 的统一智能体画布：把需求会话、多智能体团队、成员任务与发言、依赖 DAG 编织进同一张可交互时间轴，让 Agent 从“后台运行”变成“可视化协作”。
- Stars
- 19
- Forks
- 2
- Issues
- NaNm
- Update
- 9 days
REVIEW SCORECARD
Review Scorecard
8.0/10Average
License compliance9.0
Engineering quality6.4
Content completeness7.0
Repository scale7.0
Maintenance activity9.0
✓ No risk detected · Automated scan results are for reference only, not an official endorsement
PROJECT READMEREADMEExpandCollapse
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Open repositoryPROJECT TOPICS
Project topics
VALIDATION LADDER
Validation progress
01Store discoveryPassed
02ClassificationPassed
03Structure checkPending
04Sandbox validationPending
FAQ
Frequently Asked Questions
What is dsh-flow used for?
dsh-flow —— DeepSeek Harness 的统一智能体画布：把需求会话、多智能体团队、成员任务与发言、依赖 DAG 编织进同一张可交互时间轴，让 Agent 从“后台运行”变成“可视化协作”。
How popular is dsh-flow?
dsh-flow has 19 stars and 2 forks on GitHub, last updated 2026-09-15.
What license does dsh-flow use?
dsh-flow is distributed under the MIT license.
Is dsh-flow compatible with DeepSeek Harness?
dsh-flow is listed in the DSH Universe directory as a tool for DeepSeek Harness. This plugin is listed in the DSH Universe directory and covered by its validation pipeline.
CLASSIFICATION EVIDENCE
Classification evidence
Project typePlugin
Feature categoryAgents & sessions
Rule confidenceMedium
The system checks GitHub Topics against the site taxonomy and keyword rules. Current matches:No valid category tags。
Agents & sessionsSkill
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Structure check pending
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Structure check pending
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Structure check pending
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Tianshu is a terminal coding agent runtime built on the harness project (Tui X Gui), with prefix-cache engineering optimization for DeepSeek V4 (measured steady-state hit rate of 97–99% in long sessions) and deep adaptation. It breaks out of the traditional AI coding assistant's limit of treating the LLM merely as a tool, and is built on a cognitive virtual machine (CVM), a self-awareness layer and Stigmergy self-decaying memory, making the AI a development partner with independent judgment and cognitive safeguards.
Structure check pending
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Deepseek Harness, Openclaw knowledge graph memory plugin. Invited to present at Tsinghua University seminar in April 2026. Knowledge Graph + Memory；Knowledge Graph Context Engine for OpenClaw — extracts structured triples from conversations, compresses context 75%, enables cross-session experience reuse
Structure check pending
claude-codecodexdeepseekdeepseek-harness